Remote Sensing on land Surface PropertiesoutlineMODIS Land Cover Classification (M. A. Friedl, A. H. Strahler et al. – Boston University)ReflectanceSlide 5MODIS multi-channelsMODIS BAND 1 (RED)MODIS BAND 2 (NIR)Slide 9Slide 10Slide 11Slide 12Vegetation: NDVISlide 14Slide 15NDVINDVI represents greennessSlide 18NDVI as an Indicator of DroughtEnhanced Vegetation Index (EVI)Electromagnetic spectrumSlide 22Spectral Surface Albedo (E. G. Moody, M. D. King, S. Platnick, C. B. Schaaf, F. Gao – GSFC, BU)Conditioned Spectral Albedo Maps (C. B. Schaaf, F. Gao, A. H. Strahler - Boston University)Indian Subcontinent during Monsoon June 10-26, 2002Spatially Complete Spectral Albedo Maps (E. G. Moody, M. D. King, S. Platnick, C. B. Schaaf, F. Gao – GSFC, BU)Spectral Albedo of SnowAlbedo by IGBP Ecosystem Northern Hemisphere Multiyear Average (2000-2004)Slide 29Surface Temperature: Skin TemperatureSlide 31Slide 32Slide 33MODIS SST AlgorithmMODIS SSTAccuracy of Retrieved TskinSlide 37Slide 38Slide 39Slide 40Slide 41Land Tskin vs AlbedoLand Tskin vs. Water VaporSlide 44Slide 45Slide 46Slide 47Slide 48Slide 49Emissive BandsSlide 51NIR and VIS over Vegetation and OceanSlide 53Slide 54Slide 55Slide 56Slide 57Planck Function and MODIS BandsMODIS BAND 20MODIS BAND 31Slide 61Temperature sensitivityPlanck’s function (review lecture 1 )Slide 64Slide 65Slide 66B=Bref(T/Tref)  B=(Bref/ Tref) T   B T Non-Homogeneous FOVSlide 69Consequences: Cloud & Fire DetectionSlide 71Conclusions: Vegetation DetectionRemote Sensing on land Surface PropertiesMenglin JinModified from Paolo Antonelli CIMSS, University of Wisconsin-Madison, Paolo Antonelli CIMSS, University of Wisconsin-Madison, M. D. King UMCP lecture, and P. MentzelM. D. King UMCP lecture, and P. Mentzeloutline•Reflectance and albedo•Vegetation retrieval •Surface temperature retrieval•Theory of clouds and fire retrievalMODIS Land Cover Classification(M. A. Friedl, A. H. Strahler et al. – Boston University)0 Water1 Evergreen Needleleaf Forest2 Evergreen Broadleaf Forest3 Deciduous Needleleaf Forest4 Deciduous Broadleaf Forest5 Mixed Forests6 Closed Shrublands7 Open Shrublands8 Woody Savannas9 Savannas10 Grasslands11 Permanent Wetlands12 Croplands13 Urban and Built-Up14 Cropland/Natural Veg. Mosaic15 Snow and Ice16 Barren or Sparsely Vegetated17 TundraReflectanceReflectance•The physical quantity is the Reflectance i.e. The physical quantity is the Reflectance i.e. the fraction of solar energy reflected by the the fraction of solar energy reflected by the observed targetobserved target•To properly compare different reflective To properly compare different reflective channels we need to convert observed channels we need to convert observed radiance into a target physical propertyradiance into a target physical property•In the In the visiblevisible and and near infrarednear infrared this is done this is done through the ratio of the observed radiance through the ratio of the observed radiance divided by the incoming energy at the top of divided by the incoming energy at the top of the atmospherethe atmosphereSoilSoilVegetationVegetationSnowSnowOceanOceanMODIS multi-channels–Band 1 (0.65 m) – clouds and snow reflecting –Band 2 (0.86 m) – contrast between vegetation and clouds diminished–Band 26 (1.38 m) – only high clouds and moisture detected–Band 20 (3.7 m) – thermal emission plus solar reflection–Band 31 (11 m) – clouds colder than rest of scene -- Band 35 (13.9 m) – only upper atmospheric thermal emission detectedMODIS BAND 1 (RED)MODIS BAND 1 (RED)Low reflectance in Low reflectance in Vegetated areasVegetated areasHigher reflectance inHigher reflectance inNon-vegetated land areasNon-vegetated land areasMODIS BAND 2 (NIR)MODIS BAND 2 (NIR)Higher reflectance in Higher reflectance in Vegetated areasVegetated areasLower reflectance inLower reflectance inNon-vegetated land areasNon-vegetated land areasREDREDNIRNIRDense VegetationDense VegetationBarren SoilBarren SoilVegetation: NDVI•Subsequent work has shown that the NDVI is directly related to the photosynthetic capacity and hence energy absorption of plant canopies.The NDVI is calculated from these individual measurements as follows:NIR-REDNIR+REDNDVI = NDVI –Normalized Difference Vegetation IndexSatellite maps of vegetation show the density of plant growth over the entire globe. The most common measurement is called the Normalized Difference Vegetation Index (NDVI). Very low values of NDVI (0.1 and below) correspond to barren areas of rock, sand, or snow. Moderate values represent shrub and grassland (0.2 to 0.3), while high values indicate temperate and tropical rainforests (0.6 to 0.8).NDVI•Vegetation appears very different at visible and near-infrared wavelengths. In visible light (top), vegetated areas are very dark, almost black, while desert regions (like the Sahara) are light. At near-infrared wavelengths, the vegetation is brighter and deserts are about the same. By comparing visible and infrared light, scientists measure the relative amount of vegetation.NDVI represents greennessNDVI as an Indicator of Drought August 1993In most climates, vegetation growth is limited by water so the relative density of vegetation is a good indicator of agricultural droughtEnhanced Vegetation Index (EVI)•In December 1999, NASA launched the Terra spacecraft, the flagship in the agency’s Earth Observing System (EOS) program. Aboard Terra flies a sensor called the Moderate-resolution Imaging Spectroradiometer, or MODIS, that greatly improves scientists’ ability to measure plant growth on a global scale. •EVI is calculated similarly to NDVI, it corrects for some distortions in the reflected light caused by the particles in the air as well as the ground cover below the vegetation. •does not become saturated as easily as the NDVI when viewing rainforests and other areas of the Earth with large amounts of chlorophyllElectromagnetic spectrum0.001m1m1000 m1m1000m1,000,000 m = 1mGammaX raysUltraviolet (UV)Infrared (IR)MicrowaveRadio wavesRed(0.7m)Orange(0.6m)YellowGreen(0.5m)BlueViolet(0.4m)VisibleLonger waves Shorter waves•Spectral albedo needed for retrievals over land surfaces•Spatially complete surface albedo datasets have been generated–Uses high-quality operational MODIS surface albedo dataset (MOD43B3)–Imposes phenological curve and ecosystem-dependent variability